Operations | Monitoring | ITSM | DevOps | Cloud

This glossary is a bookmarkable reference for cost-per-unit metrics in FinOps unit economics. It’s designed for engineering, finance, and FinOps teams that need a shared language for understanding how cloud costs behave as usage, customers, and products scale. The terms are organized by category and include real-world context.

AWS recently experienced a significant outage. The outage took down major services, including parts of McDonald’s mobile ordering system, some Netflix features, and many other applications that relied solely on AWS infrastructure. This event perfectly illustrates why relying on just one cloud platform can be risky.

Hybrid and multi-cloud monitoring breaks down when teams can’t connect signals to customer impact fast enough to act. Hybrid and multi-cloud sound simple: run some workloads in public cloud, keep some on-premises, and connect it all. But in practice, you’re managing dependencies across teams and systems, tools that don’t share context, and incidents that refuse to stay in one place.

AWS EC2, Azure Virtual Machines, and Google Compute Engine (GCE) appear similar on paper but produce different bills due to how each provider prices capacity, discounts, idle time, and commitment terms. The same VM configuration can cost 20-40% more or less depending on which cloud you choose and how your workload runs. On paper, all three offer similar virtual machines. In reality, they price capacity, discounts, and idle time very differently.

Previously I have written about how useful public cloud storage can be when starting a new project without knowing how much data you will need to store. However, as datasets grow over time, the costs of public cloud storage can become overwhelming. This is where an on premise, or co-located, self-hosted storage system becomes advantageous: it provides the greatest range of benefits, including cost, performance, security, and data sovereignty.

Third-party data now drives forecasting, analytics, and machine learning across modern cloud teams. But acquiring it has long meant custom contracts, delayed access, and limited visibility into how data costs scale inside analytics workflows. AWS Data Exchange reduces much of that friction by integrating third-party data into the AWS ecosystem.

In regulated industries like fintech, healthcare, and government, DevOps teams often find themselves acting as human compliance gateways. The pressure to maintain strict security standards while accelerating release cycles creates a compliance tax: a heavy burden of manual environment setups, security review tickets, and the inevitable scramble for evidence before an audit. This manual labor, or toil, is more than a drain on productivity. It creates a dangerous gap between policy and actual operations.

Imagine you want to launch an application without first building and managing the servers that run it. You write the code, pick how it should run, and then let a platform take care of the rest. That’s the core promise of AWS Elastic Beanstalk. In this snackable guide, you’ll understand AWS Elastic Beanstalk well enough to decide if it belongs in your AWS architecture.

During the October 20th AWS outage, not one Control Plane customer went down. Here’s the architecture that made that possible, and how to assess your own.

IP address exhaustion in Kubernetes doesn’t announce itself with clear error messages. Pods fail to schedule, services degrade unpredictably, and the symptoms look like a dozen different problems before anyone realizes the cluster has run out of available IP addresses. By the time the root cause becomes clear, multiple services are affected and recovery requires coordination across infrastructure layers.